情感日志心情随笔,电阻手链,小鞋子观后感
|
4.0 Conclusion
As the seller's market changes into the buyer's market, companies are facing more intense competition, for enterprises, how to find target customer bases to meet the individual needs of consumers, to meet consumer spending potential and improve customer loyalty has become the largest challenge for enterprises. Network and technology progress has brought the explosion of information, information explosion on the one hand brings opportunity for enterprises to meet the challenges mentioned above, on the other hand, too much information has also brought difficulties to enterprises in collecting and dealing with right information. The emergence of customer relationship management system on the one hand has brought convenience for enterprises to deal with and gather information, on the one hand, through data results by CRM analysis provides the basis for enterprises to develop correct business strategy to deal with the challenges.
This essay was from four aspects: demographic information, brand and product, attitude and channel to developed CRM strategy for Arthurs. The first three strategies helps Arthurs to meet the needs of target consumers and meet consumers’ personalized needs through cross-selling and up-selling strategies, and thus improving consumer satisfaction and loyalty to increase Arthurs’ income, which is useful for the realization of Arthurs’ short-term goal. Implementing online and offline sales strategies is in line with the trend of retail development, helping to improve the efficiency of services and fostering long-term relationships between Arthurs and consumers, and this strategy helps to offset the shortcomings of online sales, which can attract more consumers while stimulating consumers' willingness to consume, thereby increasing the lifetime value of consumers, which is useful for achieving long-term goals for Arthurs.
Arthurs’ future implementation of CRM will encounter the following challenges. First, whether the data collected by CRM can really represent the characteristics of customer behavior and preferences, if the data only reflects the situation of part of consumers, then CRM strategy developed based on these data may not be able to help Arthurs to achieve its goals. Second, the successful implementation of the future CRM strategy needs Arthurs to invest a certain amount of resources for improving the CRM system, improving the construction of Arthurs’ shopping site, strengthening the training of staff to improve their cross-selling and sales skills, improving logistics services and network payment services and so on. Finally, Arthurs’ organizational culture needs to be changed, and its workflow needs to be optimized and reconstructed. CRM is not just technology, it also reflects the customer-centric marketing ideas, Arthurs should also establish a customer-centric organizational culture, requiring each employee to provide customer service actively, with enthusiastic attitude to respond customer consultation and to collect customer-related data and information carefully. In addition, the implementation of the CMR strategy requires Arthurs to optimize the workflow, enabling the enterprise to discover customer needs in a timely manner and have the ability to respond to customer needs with the least time and to the greatest extent to satisfy them.
References
Anderl, E., Schumann, J. H. and Kunz, W. (2016). Helping firms reduce complexity in multichannel online data: a new taxonomy-based approach for customer journeys. Journal of Retailing, 92(2), 185-203.
Artun, O. and Levin, D. (2015). Predictive marketing. Available from: http://www.ebooks.com/2130996/predictive-marketing/artun-omer-levin-dominique/ (accessed on April 15, 2017)
Chaffey, D. and Ellis-Chadwick, F. (2012). Digital marketing: strategy, implementation and practice. Pearson Education, British.
Imran, A. A. (2014). A study on AMAZON: information systems, business strategies and e-CRM. Available from:
https://www.researchgate.net/publication/261440748_A_STUDY_ON_AMAZON_INFORMATION_SYSTEMS_BUSINESS_STRATEGIES_AND_e-CRM(accessed on April 15, 2017)
Krishna, G. Y. and Ravi, V. (2016). Evolutionary computing applied to customer relationship management: a survey. Engineering Applications of Artificial Intelligence, 56(11), 30-59.
Minami, C. and Dawson, J. (2008). The CRM process in retail and service sector firms in Japan: Loyalty development and financial return. Journal of Retailing and Consumer Services, 15(5), 375-385.
Nenonen, S. and Storbacka, K. (2016). Driving shareholder value with customer asset management: moving beyond customer lifetime value. Industrial Marketing Management, 52(1), 140-150.
Pantano, E., Priporas, C. V., Sorace, S. and Iazzolino, G. (2017). Does innovation-orientation lead to retail industry growth? Empirical evidence from patent analysis. Journal of Retailing and Consumer Services, 34(1), 88-94.
Rashid, M. H. A., Ahmad, F. S. and Othman, A. K. (2014). Does service recovery affect customer satisfaction? A study on co-created retail industry. Procedia - Social and Behavioral Sciences, 130(15), 455-460.
Rezaei, J., Fahim, P. B. M. and Tavasszy, L. (2014). Supplier selection in the airline retail industry using a funnel methodology: Conjunctive screening method and fuzzy AHP. Expert Systems with Applications, 41(18), 8165-8179.
Santoso, A. S. and Erdaka, A. (2015). Customer loyalty in collaborative consumption model: empirical study of CRM for product-service system-based e-commerce in Indonesia. Procedia Computer Science, 72, 543-551.
Verhoef, P. C. et al. (2010). CRM in data-rich multichannel retailing environments: a review and future research directions. Journal of Interactive Marketing, 24(2), 121-137.
|
